Falls initiated by external perturbations such as slips, trips and stumbles are a serious health hazard to older workers. Experimental studies have provided a general description of postural responses to perturbations. However, causes of failed recovery attempts are challenging to disentangle through experiments alone due to the complexity of the postural control system and the significant degree of correlation among key gait variables. Forward simulations of postural responses during slipping will be used in conjunction with experimental data to identify subject-specific biomechanical limitations that explain why older adults slip and fall. More specifically, we will determine the extent to which the magnitude of the slip depends on gait variables that change with aging including step length and center of mass acceleration (Aim 1), strength and torque generation rate abilities (Aim 2). Finally in Aim 3, we will predict the magnitude of a slip using a multi- regression model with explanatory variables that (1) have been identified in the simulations as key variables to reduce the risk of slips and falls, and (2) can be measured in non-slippery environments. To collect the experimental data required to achieve the aims of this project, one hundred seven (N = 107) older adults between the ages of 55 and 70 years old will be recruited for participation. Subjects will walk on dry and slippery floors. Strength data will be collected in both age groups. Simulations will be based on subject- specific models of the body driven with torques generated by a physiologically motivated controller. Relevance to public health: In summary, through experiments and simulations of slipping, this project will systematically identify aging-related biomechanical limitations that predispose older workers to slip and fall. These biomechanical limitations may be the result of underlying deficits in neuromuscular control and sensory integration but they are the ultimate cause of failed recoveries from external perturbations. This fundamental knowledge is required to plan, to develop and to implement effective deficits-targeted interventions focused on minimizing the risk of falling in the workplace.